Neural networks are machine learning models that may be trained to produce outputs based on an input. Neural networks may include an output layer where one or more nodes of an output layer correspond to candidate outputs, and the value of output nodes is a probability that the candidate output is the correct output for the input.
Neural networks are often trained on general training sets. However, training the neural network on a general training set may not produce high quality outputs when the neural network is used on a more specific dataset. Therefore, it would be desirable to provide a mechanism for customizing a neural network that has been trained on a general training set for a specific dataset.